{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Feature: Intersections Weighted by Word Match "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Question intersections weighted by word match ratio (based on the [kernel by @skihikingkevin](https://www.kaggle.com/skihikingkevin/magic-feature-v2-krzy-new-idea))."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This utility package imports `numpy`, `pandas`, `matplotlib` and a helper `kg` module into the root namespace."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pygoose import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from collections import defaultdict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import nltk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to\n",
      "[nltk_data]     /Users/xshuai/nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nltk.download('stopwords')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Config"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Automatically discover the paths to various data folders and compose the project structure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "project = kg.Project.discover()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Identifier for storing these features on disk and referring to them later."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_list_id = 'wm_intersect'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Original question datasets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train = pd.read_csv(project.data_dir + 'train.csv').fillna('none')\n",
    "df_test = pd.read_csv(project.data_dir + 'test.csv').fillna('none')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Build features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_all_pairs = pd.concat([\n",
    "    df_train[['question1', 'question2']],\n",
    "    df_test[['question1', 'question2']]\n",
    "], axis=0).reset_index(drop='index')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "stops = set(nltk.corpus.stopwords.words('english'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def word_match_share(pair):\n",
    "    q1 = str(pair[0]).lower().split()\n",
    "    q2 = str(pair[1]).lower().split()\n",
    "    q1words = {}\n",
    "    q2words = {}\n",
    "    \n",
    "    for word in q1:\n",
    "        if word not in stops:\n",
    "            q1words[word] = 1\n",
    "    for word in q2:\n",
    "        if word not in stops:\n",
    "            q2words[word] = 1\n",
    "    \n",
    "    if len(q1words) == 0 or len(q2words) == 0:\n",
    "        # The computer-generated chaff includes a few questions that are nothing but stopwords\n",
    "        return 0\n",
    "    \n",
    "    shared_words_in_q1 = [w for w in q1words.keys() if w in q2words]\n",
    "    shared_words_in_q2 = [w for w in q2words.keys() if w in q1words]\n",
    "    R = (len(shared_words_in_q1) + len(shared_words_in_q2)) / (len(q1words) + len(q2words))\n",
    "\n",
    "    return R"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "Batches:   0%|          | 0/2751 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/Cellar/python3/3.6.3/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/ipykernel_launcher.py:2: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.\n",
      "  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Batches: 100%|██████████| 2751/2751 [00:23<00:00, 115.71it/s]\n"
     ]
    }
   ],
   "source": [
    "wms = kg.jobs.map_batch_parallel(\n",
    "    df_all_pairs[['question1', 'question2']].as_matrix(),\n",
    "    item_mapper=word_match_share,\n",
    "    batch_size=1000,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 2750086/2750086 [07:50<00:00, 5840.78it/s]\n"
     ]
    }
   ],
   "source": [
    "q_dict = defaultdict(dict)\n",
    "for i in progressbar(range(len(wms))):\n",
    "    q_dict[df_all_pairs.question1[i]][df_all_pairs.question2[i]] = wms[i]\n",
    "    q_dict[df_all_pairs.question2[i]][df_all_pairs.question1[i]] = wms[i]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def q1_q2_intersect(row):\n",
    "    return len(set(q_dict[row['question1']]).intersection(set(q_dict[row['question2']])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def q1_q2_wm_ratio(row):\n",
    "    q1 = q_dict[row['question1']]\n",
    "    q2 = q_dict[row['question2']]\n",
    "    \n",
    "    inter_keys = set(q1.keys()).intersection(set(q2.keys()))\n",
    "    if len(inter_keys) == 0:\n",
    "        return 0\n",
    "    \n",
    "    inter_wm = 0\n",
    "    total_wm = 0\n",
    "    \n",
    "    for q, wm in q1.items():\n",
    "        if q in inter_keys:\n",
    "            inter_wm += wm\n",
    "        total_wm += wm\n",
    "    \n",
    "    for q, wm in q2.items():\n",
    "        if q in inter_keys:\n",
    "            inter_wm += wm\n",
    "        total_wm += wm\n",
    "    \n",
    "    if total_wm == 0:\n",
    "        return 0\n",
    "    \n",
    "    return inter_wm / total_wm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train['q1_q2_wm_ratio'] = df_train.apply(q1_q2_wm_ratio, axis=1, raw=True)\n",
    "df_test['q1_q2_wm_ratio'] = df_test.apply(q1_q2_wm_ratio, axis=1, raw=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train['q1_q2_intersect'] = df_train.apply(q1_q2_intersect, axis=1, raw=True)\n",
    "df_test['q1_q2_intersect'] = df_test.apply(q1_q2_intersect, axis=1, raw=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1af352208>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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n8OlPf5olS5ZANsf+cZy6KUk1zwRAkmrM9OnZBc0mTZrEpEmTVlk2aNAgRowYwaBBg9h33335+c9/zuLFiyE7oXYFTt2UpJoXFdwBUhWIiHl1dXV1L37rR62qt8kZJ7YcJEntqF+/ftTX19fnV8cphIZt9rx581pd90MX3t8OPSpv5rcP77B1Seoa2mKb3ao7AUuSJEnq2kwAJEmSpAIxAZAkSZIKxARAkiRJKhATAEmSJKlATAAkSZKkAjEBkCRJkgrEBECSJEkqEBMASZIkqUBMACRJkqQCMQGQJEmSCsQEQJIkSSoQEwBJkiSpQEwAJEmSpAIxAZAkSZIKxARAkiRJKhATAEmSJKlATAAkSZKkAjEBkCRJkgrEBECSJEkqEBMASZIkqUBMACRJkqQCMQGQJEmSCsQEQJIkSSoQEwBJkiSpQEwAJEmSpAIxAZAkSZIKxARAkiRJKhATAEmSJKlATAAkSZKkAjEBkCRJkgrEBECSJEkqEBMASZIkqUBMACRJkqQCMQGQJEmSCsQEQJIkSSqQFhOAiPhoRPw4Ip6NiHcj4h8RcVtEbFsmdlhETImIhRHxZkRcExG9y8T1iIixETErIhZFxOMRcXAT6++0NiVJkqRaU8kIwAXAMcDDwJeB64DhwFMRsWNDUETsCvwG6AmcA1wPfB64vUyb44CzgVvyNlcAD0TEPqVBVdCmJEmSVFPWqyDm+8AJKaWlDQURcTvwV7Lk4OS8+ArgbWB4SmlBHjcT+GlEfCyl9Nu8bE/geODslNLVednNwDPAWOCAknV3WpuSJElSLWpxBCClNLV05z8vexH4G7AjQERsAHwcuLlhpzp3M7AAOK6kbCSwjOzIe0N7i4EbgP0iYmCVtClJXdKf/vQnzjzzTHbaaSfWX399ttxyS44//nheeuml1WKnTp3KggULAOqcuilJxbBGJwFHRACbAm/lRUPIRhOmlcblicN0YGhJ8VBgRqMdcIAngAB2rZI2JalLGjt2LHfddReHHHII11xzDaeffjqTJ09m6NChPPfccyvjpk+fzsEHr9zfXoRTNyWpECqZAlTOZ4DNgYvz3wfmz7PLxM4GSjfmA4E3mogD2KxK2lxFRMxralmuroXlktQhzjnnHCZMmED37t1Xlo0aNYohQ4YwduxYxo0bB8CYMWPYaKONeOedd5g/f/7SlNIlTt2UpNrX6hGAiBgM/BiYAozPi3vlz0vKVFlcsrwhtqm40rY6u01J6pKGDRu2ys4/wHbbbceHP/zhlSMA8+fP56GHHuKkk04iG9RdyambklTjWjUCEBEDgPuBfwGfSimtyBctyp97lKnWs2R5Q2xTcaVtdXabq0gp9WtqGawcIXAUQFJVSinxz3/+k4985CMA/PWvf2X58uXssccejeOWRsSaTLOcTTPTLDuozZUctZWkplU8AhARdcADZBvNQ1NKb5YsbphSM3C1ilnZrEaxTcVREtvZbUpSzbj11lt54403OO647ID57NnZ5nDgwHKbQ2bz/tRJyLaPTU2dhMqnWbZ3m5KkClSUAERET2ASsD3wyZTS841CngGWA3s0qted7CjO9JLi6cDgiOjTqI298uenq6RNSaoJM2bM4Mwzz2S//fZj9OjRACxalA149uhRbkC060/dTCn1a+4B1JerJ0lFUMmdgNclu9LCPmTTfh5vHJNSqie7UdjoRjvho4E+wMSSsjuBbsCpJevoAZwCPJpSmlUlbUpSl/fmm29y+OGHs+GGGzJx4kTWWSfb7Pfqle03L1lSbr+6NqZuSpLKq+QcgCuBI8lGAPpHxIklyxaklO7Of74YmApMjojrgS2Ac4EHUkoPN1RIKf0xIiYC38lP8noZ+CwwiPdvKkZntylJXV19fT2HHXYY9fX1PProowwYMGDlsoapPw1TgRpx6qYk1bBKpgA1XEP/CLKr/pQ+rm4ISik9CRxCNkx7FXAa8FPgU2XaPAm4Jn/+AdnR+0+klB4tDaqCNiWpS1q8eDFHHHEEL7zwAvfddx877LDDKst33nln1ltvPaZNW+XcWqduSlIBVHIn4OEppWji8aFGsVNSSvumlHqllDZNKX0ppfRumTYXp5TOTykNTCn1TCnt2dTR985sU5I6yo477siVV17JnDlz1rqt9957j1GjRvHYY48xceJE9t5779Vi6urqOOSQQxg/fjwppdJFTt2UpBq3pjcCkyS1oZQS559/PmPGjOGII47g1FNP5dBDD218jf6KnHvuudx7770cccQRzJ07l1tuuWXlsj59+jBixAgALr/8coYNG8by5csBukfEZTh1U5JqngmAJFWBGTNmMGXKFG644QbuvPNOfvGLX7D55ptzyimn8LnPfY5BgwZV3Nb06dmsmEmTJjFp0qRVlg0aNGhlArDbbrvx8MMPM3z4cMiuptMwJfKiMs2eBHwzf94Q+AtNTLOMiEPI7uZ7FTC/g9uUJLUgGg39ag1FxLy6urq6F7/1o1bV2+SME1sOklQoCxYs4H//93+54YYbeOKJJ1hnnXX42Mc+xqmnnsrRRx9Nt27d2nR9/fr1o76+vr6lGx7WkoZt9rx5Ld0vbHUfuvD+duhReTO/fXiHrUtS19AW2+yKbwQmSeoYffr04bTTTuPxxx/nmWee4bjjjuPhhx/m05/+NJttthnnnXcer7/+emd3U5LURZkASFIVWrFiBZMmTWLMmDFMnJid57r//vuz2267cdVVVzF48GDuu+++Tu6lJKkrMgGQpCry4osvctFFF/HBD36Qo446iqlTp/LlL3+ZGTNmMHnyZH7961/z7LPPsu2223Leeed1dnclSV2QJwFLUhX42c9+xo033siUKVMAGD58ON///vc55phjVpvzv8MOO/Cf//mfnHbaaZ3RVUlSF2cCIElV4JRTTmGTTTbhvPPO47TTTmPbbbdtNn7HHXfk+OOP76DeSZJqiQmAJFWBO+64g6OOOqriK/zstdde7LXXXi0HSpLUiAmAJFWBkSNHdnYXJEkF4UnAklQFvvGNb7Drrrs2uXzo0KF861vf6sAeSZJqlQmAJFWBn//85w135C3roIMO4o477ui4DkmSapYJgCRVgb///e/suOOOTS7fYYcdeOWVVzqwR5KkWmUCIElVIKXEvHnzmlxeX1/Pe++914E9kiTVKhMASaoCO+20E5MmTWpy+aRJk9hhhx06sEeSpFplAiBJVeBzn/scU6dO5T/+4z+YO3fuyvK5c+dy6qmnMnXqVD73uc91Yg8lSbXCy4BKUhX4/Oc/zyOPPMJNN93Ez372M7bYYgsAXn/9dVasWMHIkSM588wzO7mXkqRa4AiAJFWJ2267jVtuuYVDDz2UHj160KNHDw477DAmTJjgFYAkSW3GEQBJqiInnHACJ5xwQmd3Q5JUwxwBkCRJkgrEEQBJqhILFy7k9ttv58UXX+Ttt98mpbTK8ojg2muv7aTeSZJqhQmAJFWBadOm8clPfpI5c+astuPfwARAktQWnAIkSVXg7LPPZtGiRdx66628+eabLFu2bLXH0qVLO7ubkqQa4AiAJFWBadOmcdFFF3H88cd3dlckSTXOEQBJqgJ9+/Zlk0026exuSJIKwARAkqrAiBEjePDBBzu7G5KkAjABkKQq8J3vfIc33niDs88+m1dffbWzuyNJqmGeAyBJVaBh+s+f//xnfvCDH7DOOusQEavERARLlizpjO5JkmqICYAkVYFRo0attsMvSVJ7MAGQpCpwyy23dHYXJEkF4TkAkiRJUoGYAEhSlVixYgUTJkzg5JNP5rDDDuPpp58GYN68eUyYMIFZs2Z1cg8lSbXABECSqsCiRYs46KCDOPHEE7njjjt48MEHefvttwHo06cP55xzDv/zP//Tyb2UJNUCEwBJqgJf//rXefzxx5k4cSIzZ84kpbRy2XrrrccxxxzDr371q07soSSpVpgASFIVmDhxIqeffjrHHnss66677mrLt9tuO2bOnNnxHZMk1RwTAEmqAm+88QYf+chHmly+/vrrM3/+/A7skSSpVpkASFIV6N+/P7Nnz25y+bPPPsvAgQM7sEeSpFplAiBJVeBjH/sYN910E4sWLVpt2auvvsqNN97IoYce2gk9kyTVGhMASaoCl156KW+//TZ77rkn1113HRHBQw89xFe/+lV22203unXrxpgxYzq7m5KkGlBRAhARAyPi2xHxSES8ExEpIoaXiZuZL2v8+HaZ2H4RcV1EzImIdyPitxGxaxPrPzIinoyIxRHxj4i4NCJWu4txe7QpSR1h++2356GHHiKlxMUXX0xKibFjx3L55ZczYMAAHnroIbbccsvO7qYkqQZUusO7A3AB8BLwF2BYM7F/Bq5uVPZM6S8RsQ5wPzAE+B7wNvBFYHJE7J5Serkk9jDgbuC3wP/L63wN2Dj/vd3alKSOtOeee/LMM88wffp0nnvuOVJKbLfdduyxxx5ERGd3T5JUIypNAP4MbJxSejsiRgC/aCb29ZTSLS20N5IsiTg6pXQ3QETcAbwAXAqcVBL7PeAp4NCU0nt57Hzgooj4QUrpxXZsU5I63K677squu5YdvKzI7Nmzueaaa/jjH//ItGnTWLBgAY888gjDhw9fJe5DH/oQr776asOvdRHRcPOBsSmlC0tjI6If8B3gaKA38EfgnJTS9Mbrj4gjga8DOwH/B9wAXJ5SWt7ebUqSWlbRFKCU0jsppbcrbTQiekRE72ZCRgKzgHtK1jEHuAMYERHd8nZ2ItvYX9uwo57777zvx7Zzm5LU5Tz//POMHTuW119/nV122aXZ2N13351evXoBLARG54/bSmNKRliPB34IfAXYlGyEdZtGsQ0jrHPJRlTvJhthvaq925QkVaY95rz/G/AusG5EvEJ2JOm6RjFDgT+n0ltdZp4ATge2BZ7L4wCmlQallGZFxOsly9urTUnqEN26dWtxmk9EsGTJkhbb2n333XnrrbfYaKONuPvuuzn66KObjN1iiy146aWXWLRo0bJmRm8dtZWkGtLWCcBfgD+QbcA3AU4Dro2I/iml0hOBB5LNv2+s4SLYm5HtrA9sVN44drN2bnOliJhXrrxEXQvLJalJo0aNWi0BWL58OS+//DLTpk1jl112YciQIRW11bdv31ate/XjJqspO8Ka77B/OiK6pZSWlYywfr7MCOvFZCOs327HNiVJFWjTBCCldGTp7xFxEzAF+GpE/CSlVJ8v6gWUO4y1uGR56XNTsaXTjNqjTUnqELfc0vSpU7///e855phjuO66xoOpa+/BBx9suPdAXUS8jKO2klTz2vU+APnRmqvJdqr3KVm0COhRpkrPkuWlz03Flt4xpz3aXCml1K+5B1Bfrp4kra0DDjiAk08+ma985Stt2u4uu+zCf/3Xf9G7d2/Itn1vkY3aXtgodCBNj5rC+yOnrR21bes2V4qIec09cNRWUoF1xI3AXsuf+5eUzeb9jXqphrJZJXE0Ezur5Pf2aFOSqsL222/PtGnTWg5shXvvvZfzzz+fbt26ASwlm5P/ONmobekOcluNsPYq+b092pQkVaAjEoCt8+c5JWXTgd1j9TPe9gIWkN1voCEOYI/SoIjYDNiiZHl7tSlJVeEPf/gDPXv2bDlwLThqK0nF0GbnAEREf2BeSmlFSVlP4HzgHeCxkvA7yU4AO4rscm5ExMbAp4B7UkrLAFJKf4uIGcDpEXFDyQlgZwArgJ+3c5uS1CEmTJhQtnzu3Lk8/PDDTJo0iVNOOaUjutJWo7aNp+wMBKa2c5uSpApUnABExCX5jzvmz6MjYj+ynf4fAUcCF0fEncBMYCPgs8D2wBkppQUlzd1JNsx8c0R8j2ze6RfJRiS+3mjV5wP3Ar+OiNuBnYGzyK7j/0I7tylJHeLEE08kIspekWfdddfls5/9LFdd1SGXvW9q1HZYRESjk3abG2F9siGomVHbtm5TklSB1owAfLPR75/Ln18FfgT8FZhBdhOZTcjmaz4JnJtSuq+0YkrpvYj4BPBd4EtkczifAE5KKb3UKPa+iDiG7LrQPyT7UrqscX/ao01J6igPPfTQamURQf/+/dl6663ZYIMN2nR9c+fOpV+/fqyzzvszQR21laRiqDgBSCk1e4ealNKfgSPvxixWAAAgAElEQVRa0d6/gFPzR0uxd5N/QXR0m5LUEQ4++OA2be+yyy4D4LnnngNg/PjxTJkyhX79+nHWWWdx7733cvnllzNy5MiGm4v1AJ7GUVtJqnntcSdgSVIn++pXv7rK7zfeeCMAgwYN4qyzzmLIkCEMHjyY8ePHs3jxYshOqJ2No7aSVPNMACSpCpx++umtrhMRXHvttWWXtXR33913351JkyYB0K9fP+rr6+tTSsObinfUVpJqhwmAJFWB66+/noarGDfeeW+uvKkEQJKkpnTEfQAkSS2YNWsWu+66K5/85Cf5/e9/z1tvvcVbb73F7373Ow4//HCGDh3K7NmzWbZs2crH0qVLO7vbkqQuyARAkqrAhRdeyMYbb8w999zDfvvtR//+/enfvz/7778/9957L/379+eCCy5g3XXXXeUhSVJrmQBIUhW47777OPLII5tcftRRR3Hfffc1uVySpEqZAEhSFVi8eDGzZs1qcvkbb7zRcLUeSZLWigmAJFWBYcOG8cMf/pCpU6eutuzRRx/lhz/8IcOGDeuEnkmSao1XAZKkKvD973+f/fffn/3335+9996bwYMHAzBjxgwef/xx+vbty5VXXtnJvZQk1QITAEmqAjvvvDPTpk3joosu4v777+exxx4DoFevXhx77LFcccUVbLvttp3cS0lSLTABkKQqsc0223DHHXfw3nvv8eabbwIwYMAAr/YjSWpTJgCSVGXWXXddNt98887uhiSpRnkSsCRViQULFnDFFVcwfPhwdtxxRx5//HEA3nrrLa644gpeeOGFTu6hJKkWOAIgSVXg7bffZr/99uPFF19kq6224pVXXmHhwoUAbLzxxlx//fXMnTuX733ve53cU0lSV2cCIElV4JJLLuGNN97gscceY6uttuIDH/jAKstHjBjBww8/3Em9kyTVEqcASVIVmDRpEl/84hf56Ec/SkSstnyrrbbitdde64SeSZJqjQmAJFWBOXPmsN122zW5fL311ls5JUiSpLVhAiBJVWDTTTfllVdeaXL5U089xZZbbtmBPZIk1SoTAEmqAp/4xCe44YYb+Oc//7nasmnTpnHzzTdz5JFHdkLPJEm1xgRAkqrA1772NSKCoUOH8tWvfpWI4JZbbmH06NHst99+bLrpplx44YWd3U1JUg0wAZCkKrDZZpsxdepUhg4dyrXXXktKiXHjxjFhwgQOOugg/vCHP7DRRht1djclSTXAy4BKUpXYaqutuP/++5k7dy7PP/88KSW23Xbb1S4JKknS2nAEQJI62YIFCzj99NO58847Aejfvz/77LMPw4YNc+dfktTmTAAkqZP16dOH8ePHU19f39ldkSQVgAmAJFWBnXbaiVdffbWzuyFJKgATAEmqAueffz4/+clPePnllzu7K5KkGudJwJJUBV555RW22GILdt55Z4488ki22247evfuvUpMRHDRRRd1Ug8lSbXCBECSqsAll1yy8ueJEyeWjTEBkCS1BRMASaoCL774Ymd3QZJUECYAktRJnnjiCbbddlv69+/PNtts09ndkSQVhCcBS1In2WefffjVr3618vcFCxZwwgkn8Oyzz3ZiryRJtc4EQJI6SUppld+XLFnCbbfdxptvvtlJPZIkFYEJgCRJklQgJgCSJElSgZgASJIkSQXiVYAkqRP98pe/XDnnf+HChUQEEydOZPr06avFRgRnn312R3dRklRjTAAkqRNNmDCBCRMmrFJ27bXXlo01AZAktQUTAEnqJI888khnd0GSVEAmAJLUSQ488MDO7oIkqYA8CViSJEkqkIoSgIgYGBHfjohHIuKdiEgRMbyJ2CMj4smIWBwR/4iISyNitZGGiOgXEddFxJyIeDcifhsRu1Zbm5IkSVItqXQEYAfgAmAL4C9NBUXEYcDdwFzg/+U/fw24qlHcOsD9wPHAD4GvAJsCkyNim2ppU5K6otmzZ3PhhRdy0EEH0bdvXyKCyZMnl4299957eeeddwDqPGgjScVQ6cbzz8DGKaW3I2IE8Ism4r4HPAUcmlJ6DyAi5gMXRcQPUkov5nEjgWHA0Smlu/O4O4AXgEuBk6qkTUnqcp5//nnGjh3Ltttuyy677MLUqVPLxj3wwAOMGDGCddZZB2AR7x8M2Zjs4AiwygGWIWTbz7eBL5IdYNk9pfRySWzDAZbf5m0M6ag2JUmVqWgEIKX0Tkrp7eZiImInYCfg2oad6tx/5+s5tqRsJDALuKdkHXOAO4AREdGtStqUpC5n991356233uLFF1/k/PPPbzLuvPPOY+jQoay//voAS1NKXwK+BXwxIrYrCW04wHJSSukbKaUfA8OBRHaApVTpAZafdnCbkqQKtOVJwEPz52mlhSmlWcDrJcsbYv+cUkqN2ngC6AtsWyVtSlKX07dvXzbaaKNmY5599lmeffZZPv/5zxMRpYs8aCNJNa4tE4CB+fPsMstmA5s1im0qjpLYzm5zpYiY19wDqCtXT5Kq0VNPPQXAHnvssUq5B20kqfa1ZQLQK39eUmbZ4pLlDbFNxZW21dltSlJNmj07OwYycODAsovxoI0k1ay2vILCovy5R5llPUuWN8Q2FVfaVme3uVJKqV+58gZ+oUjqShYtyjZ1PXqU2xSyGOhd8ntbHWBp7zYlSRVoyxGAhqMz5Q4nDSSb61ka21QcJbGd3aYk1aRevbL96iVLyu1X18ZBm+YeQH25epJUBG2ZAEzPn1eZUBoRm5HdP2B6o9jdo9GZZ8BewALgpSppU5JqUsPUn4apQI0X40EbSapZbZYApJT+BswATo+IdUsWnQGsAH5eUnYn2bzNoxoKImJj4FPAPSmlZVXSpiTVpF13ze63NW3aKufWetBGkgqg4nMAIuKS/Mcd8+fREbEfMC+l9KO87HzgXuDXEXE7sDNwFtnl214oae5O4HHg5oj4HvAW2Q1g1gG+3mjVndmmJNWkD3/4wwwePJjrrruORhfiaeoAy0iyAywNN1ose4AlIhoOsNxQctnOjmpTklSB1pwE/M1Gv38uf34V+BFASum+iDiG7CYuPwTmAJc1rptSei8iPgF8F/gS2UleT5DdEOalRrGd1qYkdVWXXXYZAM899xwA48ePZ8qUKfTr14+zzjoLgO9+97sceeSRDXcC7h4R1+BBG0mqebH6JZi1JiJiXl1dXd2L3/pRy8ElNjnjxHbqkaQiW31mTWbQoEHMnDlz5e933303xx57LCtWrIDsuvo3At9MKS1v1N6GZAdYRvD+AZZzU0pPlln3CLIDLDuSHWDpsDYr1bDNnjdvXqvrfujC+9dklWtk5rcP77B1Seoa+vXrR319fX1LV6hsTlteBlSSVCUqPbgzYsQI+vbt2/Bl8sFm2vsXcGr+aGndd5NP62khrs3blCS1rC2vAiRJkiSpypkASJIkSQViAiBJkiQViAmAJEmSVCAmAJIkSVKBmABIkiRJBWICIEmSJBWICYAkSZJUICYAkiRJUoGYAEiSJEkFYgIgSZIkFYgJgCRJklQgJgCSJElSgZgASJIkSQViAiBJkiQViAmAJEmSVCAmAJIkSVKBmABIkiRJBWICIEmSJBWICYAkSZJUICYAkiRJUoGYAEiSJEkFYgIgSZIkFYgJgCRJklQgJgCSJElSgZgASJIkSQViAiBJkiQViAmAJEmSVCAmAJIkSVKBmABIkiRJBWICIEmSJBWICYAkSZJUICYAkiRJUoGYAEiSJEkFYgIgSZIkFYgJgCRJklQgJgCSJElSgZgASJIkSQXSpglARAyPiNTEY3Cj2GERMSUiFkbEmxFxTUT0LtNmj4gYGxGzImJRRDweEQc3sf42b1OSJEmqJe01AnA1MLrRY1bDwojYFfgN0BM4B7ge+Dxwe5m2xgFnA7cAXwZWAA9ExD6lQe3RpiTVssmTJxMR1NfXA9R50EaSimG9dmr3dymlu5tZfgXwNjA8pbQAICJmAj+NiI+llH6bl+0JHA+cnVK6Oi+7GXgGGAsc0M5tSlLN6969O0uXLl1IdtCkQbmDNn8jO8CyBXAesDVwRKPmxgHHkh0Iegk4mewAy4Eppcfas01JUmXaKwEgIvoCi1JKyxuVbwB8HPhuw4567mbgKuA44Ld52UhgGdnRfABSSosj4gbg8ogYmFKa3R5truXLl6QuY7311mPp0qXLUkq3NBHiQRtJqiHtNQVoPDAfWBQRD0bEkJJlQ8gSj2mlFVJKS4HpwNCS4qHAjEY79QBPAAHs2o5tSlKhRMRqB4VKDrDcXOYAywKyAywNyh5gAW4A9ouIge3VpiSpcm2dACwF7iSbV38U8F/AnsCUiNg+j2nYWJc7yj4b2Kzk94HNxFES2x5triIi5jX3AOrK1ZOkardw4ULItmEetJGkAmjTBCClNDWl9KmU0o0ppXtTSpcBBwK9gUvzsF7585IyTSwuWd4Q21RcaVvt0aYk1bTu3bszcuRIevXqBfAuHrSRpEJo9/sApJSeBh4GGq7YsCh/7lEmvGfJ8obYpuJK22qPNleRUurX3AOoL1dPkqrVsGHDmDhxIt27dwdY7kEbSSqGdjsJuJHXeD8BaDhqU27e5kBKrjyRxzYVR0lse7QpSYWTUno6ImrioE258gaOAkgqso66E/DWwJz852eA5cAepQER0Z1sLuf0kuLpwOCI6NOovb3y56fbsU1JKqrXgP75zx60kaQa09Z3At6kTNl+wEHArwFSSvVkU4JGN9oJHw30ASaWlN0JdANOLWmvB3AK8GhKaVZ7tSlJBeZBG0mqYW09AnB7RNwXEWMi4vSI+AHZjvlbwNdL4i4GNgEmR8QXIuIy4EfAAymlhxuCUkp/JNt5/05+F8jTya7nPwi4oNG626NNSapZc+bMWa3MgzaSVPva+hyAu4HPAOcCGwD/B0wAvp5S+kdDUErpyYg4hOwmLleR3TPgp8BFZdo8Cfhm/rwh8BfgEymlR0uD2qNNSaplo0aNonfv3ixevBige37Q5nTKH7SZSnaA5Xqyu/aeS5kDLBHRcIBlIPAy8FmyAywnN1p9e7QpSapAmyYAKaUfAD+oMHYKsG8FcYuB8/NHh7cpSbVqxIgR3HrrrSxduhSyq+kciwdtJKnmRUqps/tQEyJiXl1dXd2L3/pRq+ptcsaJ7dQjSapMv379qK+vr2/pyjm1pGGbPW/evFbX/dCF97dDj8qb+e3DO2xdkrqGtthmd9RVgCRJkiRVARMASZIkqUBMACRJkqQCMQGQJEmSCsQEQJIkSSqQtr4PgNbCmz+5rNV1BpxxSTv0RJIkSbXKEQBJkiSpQEwAJEmSpAIxAZAkSZIKxARAkiRJKhATAEmSJKlATAAkSZKkAjEBkCRJkgrEBECSJEkqEBMASZIkqUBMACRJkqQCMQGQJEmSCsQEQJIkSSoQEwBJkiSpQEwAJEmSpAIxAZAkSZIKxARAkiRJKhATAEmSJKlATAAkSZKkAjEBkCRJkgrEBECSJEkqkPU6uwOSJEm15kMX3t+h65v57cM7dH3q2kwAasiMHx/VqvjBZ97TTj2RJEkdqSMTDpONrs8EQJIk1byOPiJfyxzd6Po8B0CSJEkqEBMASZIkqUCcAiRJkjqF03KkzmECIEmSpKrlOQdtzylAkiRJUoE4AiAAJv+0ddnu8NMctpWkWuOUHKkYHAGQJEmSCsQEQJIkSSoQpwBprd1507+3Kn7kKb9qp55IkiSpJYVNACKiB/ANYDSwIfA0cHFK6Ted2jFJ0mqKus12Tr6k9lDYBAAYBxwLXA28BJwMPBARB6aUHuvEfhXKteMPbVX850f/up16IqnKjcNttqQO0JGJd2ddcrSQCUBE7AkcD5ydUro6L7sZeAYYCxzQid1TK3z9jtYlEF8/zgRC6mrcZktS2ypkAgCMBJYB1zcUpJQWR8QNwOURMTClNLvTeqcOcdg9x7Yq/oGjfr7y50/84rJW1f3l0Ze0Kl7SKtxmS1IbKmoCMBSYkVJa0Kj8CSCAXQG/TNQuDr/rJ62Kv/+YM1b+/Mk7b231+u4b+ZmVPx9556RW1b135BErfz7651NaVfcXx+7XqnipGW6zJakNRUqps/vQ4SLiGeCNlNKhjcp3Av4GnJpSuqHRsnktNFsHsEGv3q3rS/duK39OS5e0qm5Wv8fKn1csfbdVddfpvv7Kn5e3su56JXWXtbJut5K6S5e1rm73buuv8vviVtbvWVL/3WULW1V3/W7v/2/fXda6/9X63d7/P727bGkr63YvqbusVXWz+u+/x95dtryVdd8/RvDusvdaWXfdlT8vXLaiVXV7d3v/CsVLl7VuG9W9W6z8eXkr6wKsV1L/vaWtq79u9/frpiWtqxs9Suu27m8dPd7/W6elrfsfA8xf9C5ASilV5aWh23ObXVdX1+r+zF/c+r+xJJWzQc/WH4uvr6+HtdxmF3UEoBdQbg9uccnyNZHmL1o4v0x5wzdM/WpLFlXUbjP1F69WVHnd1Yuqve6iMs21pv6Slus3Wbd+requ+f+pvuU3SdN/66YKK15316tb2Ueq+b/ZGtdteeVN123xLdJOdTMbAK3L0jpWu22z6+vry22zm7M2751q52vrumr59dX0a6vPtmytfW1rvc0uagKwCOhRprxnyfJVpJT6renKGo5ErWkba1O/aHU7c91dsW5nrtvX3DXqVokO3WY3pwb+lk3ytXVdtfz6fG3toyqHezvAbGBgmfKGslkd2BdJUvPcZktSGypqAjAdGBwRfRqV75U/P93B/ZEkNc1ttiS1oaImAHcC3YBTGwryu0yeAjyaUvJokiRVD7fZktSGCnkOQErpjxExEfhORAwEXgY+Cwwiu7ukJKlKuM2WpLZVyAQgdxLwzfx5Q+AvwCdSSo92aq8kSeW4zZakNlLYBCCltBg4P39IkqqY22xJajtFPQdAkiRJKqRC3glYkiRJKipHACRJkqQCMQGQJEmSCsQEQJIkSSoQEwBJkiSpQEwA2lFE9IiIsRExKyIWRcTjEXFwhXUHRsS3I+KRiHgnIlJEDK+w7kcj4scR8WxEvBsR/4iI2yJi2wrq7hERv4iIV/M+vxkRv4qIYZWsu0x7X8n7Pr2FuOF5XLnH4Fas76MRcX9E/CsiFkTE0xFxcgt1xjWz7hQRm7dQf7uIuD0iXs//3s9GxIX5nUpb6u/eEfGbvK/1EXF3RGxTJq7i90NEHBkRT0bE4vx//938fdhs3Yj4QkTckf/vU/53aXG9EbFRRJwfEX+IiDkRMS8iHouI0yqoGxFxbUT8Ja/X8D/7UkR8sLWfgYgYFBEL89gbK3jNM5v4nz/WQr+be7+miHilhfX2jIgxEfFc3t/XImJCROxbyWuOiLrIPuOz8//zCxHxYDTzmY+I3hFxZkQ8lNd7J3+ffCEi1m3u71oEsXbb683zz868iJgf2ed4q/buc6XW9LVFxDGRbdv+nr9PZ0S2PanriH5XYm3+b43a+WX+ebu6Pfq5ptb29UXECRHxRL5dmBsRv4uIPduzz5Vay8/cIRExOSLejuz7/rGIOK69+1ypWIt9uLz+jpHtey3I/28/i4iN27KPhb0PQAcZBxwLXA28RHbHygci4sCU0mMt1N0BuCCv9xegNTvgFwD7AhPzugOAs4CnImLPlNJzzdTdhux98VNgNtAP+Azw+4g4LKX0UKWdiIgBwCXAu63o+9XAnxuVzapwfYcB9wCTga8Cy4DtgQ+2UPVa4OHGzQH/A8xMKb3RzDo3B54A6oEfAXOB/YFvAR8GRjdT96PA74CZwKVkCfkXgT9ExNCU0j9Lwit6P+R/g7uB3wL/DxgCnJO33dJ76UJgg/z1DGjFevcBLgd+CVwGLCd731+XL2+u7jrAbsCDwN/zuvuQvQ8OB/6tgn6X+h6wIv/5lArr/jlfX4MdgTEt1H2O8v/bLwEfJfsMNbfe8cAIsr/RU8AWwJlkr3mD5tYdEesBDwEfIXvPvUT2Oft4Xv59yn/mtwZ+CPwmj5kPHAr8JO/zfzTR16IYxxpsryOiD/AI0Jfsc7AcOBuYHBG7ppT+1c79rsQ41uy76Dqy7e944B9k25MvAYdFxB75vRk62zjW/HsWgIg4HDigvTq4lsaxhq8vIi4j236PJ/tfrk+23RjQXL0ONI41+8x9ErgXmEr23QlwPHB7RPRNKd3Qnp2u0Brvw0XEFsDvgXlk30V9gPOAIRGxV0ppWZv0MKXkox0ewJ5AAv6zpKxn/mb4fQX1+wIb5T+PyNsaXuG6hwHdG5VtBywGxq3Ba+kNvAnc18p648h2RCcD01uIHZ6/xhFr+PeuA/4JXNNG/7/98v6MaSHugjzuw43K7yRLQLo1U/cB4C1gw5KygcA7wNVr8n4A/ka2Q7tuSdl3gPfy90BzdQfx/qWB5+X/vxbXC2wFDGpUFvn/fSHQaw3ewz8g25HfvtLPQP4eWkKWhCTgwAr+XjOBu9fkb91EH14CXmrh77VpXv7dRuWfzMvPaqH+qLz8pJKyYcDP889A97xslc88sHHj92lefmPe3lZt8dnpig/WYnsNfCV/rw4tKRtMlgh8o4u/tuFlyk7K2zu5K7+2kvjuwAvA1/K2rm6PvnbC/25Y/r48urNfRzu8tgeAN4AeJWU98rLfdfZry/uzNt8j/w0sADYvKTskb+NzbdVHpwC1n5FkO4DXNxSk7GjJDcB+ETGwucoppXdSSm+vyYpTSlNTSksblb1ItnO44xq0txCYQzYaUJF8iPFEsqPPrRIRffOjnK1xAln/vlbSRrR23Y3aS8CEFuI2yJ//2aj8TbL//3vN1N0XeDCVHCFMKc0mGxVYZSizkvdDROwE7ARcm1IqXe/VZEfaj22ufkrp1ZRvaVqz3pTS31NKrzYqS2Q7pL2ADzVXvwmvkiURK1oKBMinsFzD+0fEIRuVqUg+FN0b1vyzl7/ntyE72tac5t4zkCWFzdmX7L15R0NBSmkq8L/AB4CD8rJVPvMppbdSSn8r094v8ueKp9rVoLXZXo8EHk8pPVVSdwbZSEs1TElY49eWUppcprjh/dLq75J2sFbfs7kvk22nvtcuPVw7a/P6vgz8KaX0i4hYJx+pqiZr89o2AP6VUlpSUncJ8C9gUft0t3XWZh+O7Lv63lQy+yCl9DBZotpm2xQTgPYzFJiRUlrQqPwJsh2bXTuyM/nO8Ka0vHPREN83IjaOiB0i4gpgZ7IvtErX9UPgZymlZuf+lzGebGrCosjmNA+psN4hwAzgExHxWt7G3HwOXqvmN0dEN7IP2dSU0swWwn+XP98QER+JbN76Z8iGMsemlJrbge1B+Y3VQmBghV9epYbmz9NKC1NKs4DXS5Z3lIZh5hbfcxHRLX+/fTAijiYb7nyFbFpQJT4PbA58cw36+W9k09TejYiXI+L0NWgDsqlyALe2EPd34DXg3Ig4IiK2iIi9yRKY58imsTWnB9nR5aWNyhfmz7tBqz7zFf+fatgaba8jYh1gFxp95krqbt+QWHaitv4uqqb3y1q9tnya6lfJRnoXNhfbSdbm9R0M/Cn//q4H3onsnKfPNFOnI63Na/sd8OGI+GZEbJM/vkk25ffK9ulux8inFX+AprcpbfY97jkA7Wcg2XBUY7Pz5806sC+Q7ZxsDlxcYfxNvH/EeCnZfPgrKqx7EtmR6BGt6N9SsmkzDdNidiHbCZwSER9NKb3QQv1tyeb6jyOb8vIU2ZSKC8iGFf+zFX05FNiIlnfkSCk9GBFfJZund2TJoq+llFraGX0e2Cci1mlIFCKiO7BXvnwz3n+/VKIhYShXZzYd+J6LiP7AqcDklNKcCgZjDgUmlfw+DTil0UhGc+v6JnBpSmleKwd+/gL8gezIyibAacC1EdE/pfTtShvJk8xRwBMppZeai00pLY+IkWSjS/eWLHocOCCl1NIRrOeBbmRD6I+XlO+fPzf8n1v8zOfvt/8EXmb1c2+KZE231/3JErKmPnORt/3y2nZwLbT1d9EFZCObd61Np9rI2r62b5F9nm5py061oTV6fRGxIdl32PFk/6sLyM5POxO4JSIWppR+Ua5uB1qb/93lZKOtF5Od/wTZlJkjUyvOU6xSLX2PfyAi1q3ku7ElJgD/v71zj5WrquLwtygCjVADDTZiqRUDmkgwREBIeBhAawPcClpBirxsqiLBBynSUAWMQcpTLNAm/iEWi/RFtbVAKwpiyyPyKFQNqLWNlRSLiJRXSdos//jtwz2dzsw5Zx733nbWl0zm3jOzzt77zH6uvdba3WM4skeuZUvu8wHBFEXnNmAlxeYJGVcj59jRyNlxTzTpqFemfFr7ANcC1yZzllIkE4ZHcpeWmNlSNBG8kn7taiP2BvYFLnf3GenaPWnb8yIz+4G7l9VYnY22JucXfTGxDtm7LwZeRo6cV5vZS+4+u4nc7cgB8ydmdiPakZtOfwdQtY5k329U7wZEE5m0onORX8YlJcUeQ06s7wFORNqfslvW3wc2oUVqJdw9v2jDzH6K2sl3zWxWhVudhLTtZRfJr6BF6nzgcbSAnQYsNLNx+a3tOtyFTN3uMLOLkcnTp5EDOcDwCm3+VmTKMb5gt2pXp9X+uqjNNZMdKDo2FpnZ2chZ/IfuPpiLmoyWy5ZM9s5FvkLe6HuDTKvly/rOkcDR7v44gJktRv3F9+g35Ros2qmXbyOlzQJUjmHAFGC+mZ3k7n/sZEYHmLJ9Su3OSWViAdA93kKT5lr2yn3eddIW5zI04ZhYdpB39zXAmnSPn6OJ+B3Ibq8Z05E2/6YWs5zPwzNm9gCaXBWRPc9f1FyfC0xE2tJ7i26SFgwTgOVl7PfM7Cy0UDokmdqAFh67ATeY2TxvEAXE3Web2YHAVODCdPkJtINxBdUbePYMGtW7gbKNnIk0+pNSPSokLc6ySEyLzOwy4DdmdrC7v9hIzswOBb6KND9b28w37r7NFAbwbhSNqCyTkKZtXtEXTSEU/4AmUTBl/bAAAAf5SURBVLfkrj+BFpLnoihcjfL4opn1oYl9pu3ajKI+/Qz5TRS2eTObinY8prn78qJ87+K02l8XtblmsgNFR8YiMzsO2WcvQ2YzQ4GWypbM424BFrn7yi7lrRO0Wy/XZZN/kJ28mS0EvmFme9cxvxlI2qmXM9GYfmRu93w+8nn6EfKT2lkZsD4lfAC6x0b6Nbl5smulQlu2Q5po3Ie0quOaTaSa4Qo59SvgDDNrplF5HzInuA0YZWZjzWwsqrR7pP/3rZj8BrTNXkS221DrWJn9XzbdzyJNeaH5T+Ii4Mnc5D9jCf0h1xri7lcgzfFxwGHufiRql051s4HsGTSqdwNR565Ez+Qyd69djFVhIdJiTSj43jXAU8BfcvUti5V8QFpgVWVDei9T70ht4nTgAd8+dGsjPod+87z5D+7+ezSRLxy83P1hFNbzcBSx6v30mwONp6DNm87GmAHcVsXUaRem1f76v0hT10jWqWbG1w3aHovM7GOovj4LnNkJ84MO0WrZTkcTyFlZv5H6DoAR6f/B3rmB9utlvf7o38g0bbDPcmipbMlscTKKSviOciPNU+4DjrLqQUSGEkXj+KZOtb9YAHSP1cBH6njeZ/bdz3QzcTPbC9lUHwKc6u7Pt3nL4ajT2KfJd0ahkGozkFlM9voEMjNYh2wRq3AQikBURGa/XHto1+j0XuYeIE3u69RMzpowCm0/1vKu9F7YEbn7K+6+MqctPxnZkr9WMg8ZmcP1EfmLZnYAeg5VHbIrYWZfB64Cbnb3diNqZINv0SA1BsWwz9e369Nny4BWtoIPSu9l60wfahdlF42j0vt29SZpJYdRcmfW3be5+2p3X5U0eZ9JH42kSZs3swko8sYiypto7eq01F+nCcgaatpcTvZvQ8C5tK2xyHQw4f3IzO4Ud69yrku3abVsY9D853ds33eAzg9ZB5zQ2ay2RDv1cjU7joegsWAbWiQMJq3+diNRH9lo3N0dzVV2SlLkn5eo36ccRQfH8VgAdI+FqDJOzi6YToa9AFhVR2PcMZJD4jxkwjDR3R8rEMnL7l/n2ghkRrPB3Tc1EV+HNCu1rz+jeOunA3MqpHssCmlYxjxhQXp/5zCjNKGajCK8FD6DlIeTgcUVBu2/AkfYjqf3fhF1ss+WvE+WhzPRhLbyaZQpxONzwJSayEdfQ2Yhi6resywp3z9Gk+BLK8jtZ/WjNGXtpsgx9VvsWN9mps++jaIxNUt7t5preyGTrNeAUocIIZ+RNylvU5s5tJ9Vc70P7Ro9TUXMbBTyvXHg843avJkdj8ybHgbO6XG7/zyl+mszG2M7nky+EDjazA7PyX4Y+bIsYPBpuWzJhHQF6j/GVfCjGihaLdtS6o9VAL9Ofz/V9dwX0069XAAcaGafysmOoD/C3WCbprVatk3onJozTBH7Mtm9gdOAP3mnDsoaACxFMaq5vAjoM0UEyr53ElLodqxP2Zm3SYY07v64mS0ArkumMWuB89BhS+eXuYeZZd7tWbzlL6VJ8f/c/dYmojeiycRSYD8zOyf32evu/ssmsvPMbAtyyH0RRda5AGkNaics2+Hur6JTaGvL8U1ga4l030zp/geFHZ2S/r6qWbop7SfNbA4wzczeizrvU5At+mXuvrnoHiiKy+6U1+SCtM3jgVVmlp0EfGq6NrvZgsnMTkTRg1Yg5+FjUN2Y6+531/l+mfowFe1eLDezeeg5Xox8C77QTNbMTqPfZGlP4LCU5glI63BAPdnkTDcnleG3wCTrj8QzATmdjWmQbh8w3czuQW3k3cihdRzS4B9jZsc0yre7P1jnOWXnVXwo3a9RmfuAK5JN7HqkWToPdbJLkDlb07ZnikA0HtkSv56uFf1OS9Gi+Goz+yByAj4Y/U4voDY7vVnaZrYSOfj+HYVl/A7aNXmABm3ezD6QyuVo8J1o20dMesTd/1H7PHuBCv31HNQe8g/uduRLca/JmX8rWnxuBG7ufu6b02bZ7kc7Yteh2OzH5j5b6yVP2u0WrZYtOTDvYGKZ2sPagrFqwGjzt5uFJteLzOxm5BP0ZXRezrTu5745bfx228zsBnTg46MmH8VhqGyjUfTAIUHJMTsLrz42J3oNUro+aGYzkTnsVLQrUleJ2hI+BE5M21VfyPb9ejQQbEExXE+uIO8NXusL5B5qQ/bCJL8JRcJ5CU1YTmjjOTxE8UnAl6CJ0Msp3RfQCaVjKqSzBwoH+U/kiPwc8JUK8o8i+8hhZWWSXOZgvDGl+zxwedF90KRvRXrGW5ApwSXAbu3UB+TH8HS65wYU0alQFjl5N/peQ1nUWVeRy8seiqLarEOOTW+gxdulSDtUuR6XyE+W9sdT3f4XspfdnOrqqWXTRecPOHBald8J+aTclOrKllQH7kKDXxn5W9A5CW+jhfrGEuX9ZMFzOb+d/m5nf1Giv071w+vIjkaauVfR7tES4KDBLlO7ZSuoL3cMdrna/d3q3MsZQicBt1s+pBy4Eymm3kJKg+MHu0wdKtvZaM7wCtqBfYwhdupxyb58PXXGM+CjyPrhjVTGO4H9O5k/SwkFQRAEQRAEQdADhA9AEARBEARBEPQQsQAIgiAIgiAIgh4iFgBBEARBEARB0EPEAiAIgiAIgiAIeohYAARBEARBEARBDxELgCAIgiAIgiDoIWIBEARBEARBEAQ9RCwAgiAIgiAIgqCHiAVAEARBEARBEPQQsQAIgiAIgiAIgh7i/7zl1ofQecioAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 6))\n",
    "\n",
    "plt.subplot(1, 2, 1)\n",
    "intersect_counts = df_train.q1_q2_intersect.value_counts()\n",
    "sns.barplot(intersect_counts.index[:20], intersect_counts.values[:20])\n",
    "\n",
    "plt.subplot(1, 2, 2)\n",
    "df_train['q1_q2_wm_ratio'].plot.hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10547d898>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 6))\n",
    "\n",
    "plt.subplot(1, 2, 1)\n",
    "sns.violinplot(x='is_duplicate', y='q1_q2_wm_ratio', data=df_train)\n",
    "\n",
    "plt.subplot(1, 2, 2)\n",
    "sns.violinplot(x='is_duplicate', y='q1_q2_intersect', data=df_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                 q1_q2_intersect  q1_q2_wm_ratio\n",
      "q1_q2_intersect         1.000000        0.684575\n",
      "q1_q2_wm_ratio          0.684575        1.000000\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_train.plot.scatter(x='q1_q2_intersect', y='q1_q2_wm_ratio', figsize=(12, 6))\n",
    "print(df_train[['q1_q2_intersect', 'q1_q2_wm_ratio']].corr())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Build final features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "columns_to_keep = [\n",
    "    'q1_q2_intersect',\n",
    "    'q1_q2_wm_ratio',\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train = df_train[columns_to_keep].values\n",
    "X_test = df_test[columns_to_keep].values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Save features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_names = columns_to_keep"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "project.save_features(X_train, X_test, feature_names, feature_list_id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
